DB-PAISA: Discovery-Based Privacy-Agile IoT Sensing+Actuation

Internet of Things (IoT) devices are becoming increasingly commonplace in both public and semi-private settings. Currently, most such devices lack mechanisms that allow for their discovery by casual (nearby) users who are not owners or operators. However, these users are potentially being sensed, and/or actuated upon, by these devices, without their knowledge or consent. This triggers privacy, security, and safety issues. To address this problem, some recent work explored device transparency in the IoT ecosystem. The intuitive approach is for each device to periodically and securely broadcast (announce) its presence and capabilities to all nearby users. While effective, when no new users are present, this 𝑃𝑢𝑠ℎ-based approach generates a substantial amount of unnecessary network traffic and needlessly interferes with normal device operation. In this work, we construct DB-PAISA which addresses these issues via a 𝑃𝑢𝑙𝑙-based method, whereby devices reveal their presence and capabilities only upon explicit user request. Each device guarantees a secure timely response (even if fully compromised by malware) based on a small active Root-of-Trust (RoT). DB-PAISA requires no hardware modifications and is suitable for a range of current IoT devices. To demonstrate its feasibility and practicality, we built a fully functional and publicly available prototype. It is implemented atop a commodity MCU (NXP LCP55S69) and operates in tandem with a smartphone-based app. Using this prototype, we evaluate energy consumption and other performance factors.

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Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-03-07
DOI
https://doi.org/10.56553/popets-2025-0070
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.00

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article

DB-PAISA: Discovery-Based Privacy-Agile IoT Sensing+Actuation

Gene Tsudik, Young-il Kim, Isita Bagayatkar
Proceedings on Privacy Enhancing Technologies
Privacy-Preserving Technologies in Data
article

DB-PAISA: Discovery-Based Privacy-Agile IoT Sensing+Actuation

Gene Tsudik, Young-il Kim, Isita Bagayatkar
article en

Abstract

Internet of Things (IoT) devices are becoming increasingly commonplace in both public and semi-private settings. Currently, most such devices lack mechanisms that allow for their discovery by casual (nearby) users who are not owners or operators. However, these users are potentially being sensed, and/or actuated upon, by these devices, without their knowledge or consent. This triggers privacy, security, and safety issues. To address this problem, some recent work explored device transparency in the IoT ecosystem. The intuitive approach is for each device to periodically and securely broadcast (announce) its presence and capabilities to all nearby users. While effective, when no new users are present, this 𝑃𝑢𝑠ℎ-based approach generates a substantial amount of unnecessary network traffic and needlessly interferes with normal device operation. In this work, we construct DB-PAISA which addresses these issues via a 𝑃𝑢𝑙𝑙-based method, whereby devices reveal their presence and capabilities only upon explicit user request. Each device guarantees a secure timely response (even if fully compromised by malware) based on a small active Root-of-Trust (RoT). DB-PAISA requires no hardware modifications and is suitable for a range of current IoT devices. To demonstrate its feasibility and practicality, we built a fully functional and publicly available prototype. It is implemented atop a commodity MCU (NXP LCP55S69) and operates in tandem with a smartphone-based app. Using this prototype, we evaluate energy consumption and other performance factors.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(2)
University of California, Irvine (US)
National Science Foundation, Defense Advanced Research Projects Agency
Openalex Percentile: Top 98%
Privacy-Preserving Technologies in Data
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